System identification of Just Walk: A behavioral mHealth intervention for promoting physical activity

Mohammad T. Freigoun, Cesar A. Martin, Alicia B. Magann, Daniel Rivera, Sayali S. Phatak, Elizabeth V. Korinek, Eric B. Hekler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations


There is significant evidence to show that physical activity reduces the risk of many chronic diseases. With the rise of mobile health (mHealth) technologies, one promising approach is to design interventions that are responsive to an individual's changing needs. This is the overarching goal of Just Walk, an intensively adaptive physical activity intervention that has been designed on the basis of system identification and control engineering principles. Features of this intervention include the use of multisine signals as pseudo-random inputs for providing daily step goals and reward targets for participants, and an unconventional ARX estimation-validation procedure applied to judiciously-selected data segments that seeks to balance predictive ability over validation data segments with overall goodness of fit. Analysis of the estimated models provides important clues to individual participant characteristics that influence physical activity. The insights gained from black-box modeling are critical to building semi-physical models based on a dynamic extension of Social Cognitive Theory.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781509059928
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2017 American Control Conference, ACC 2017
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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